How PE Firms Use AI and Digital Twins for Value

The intersection of artificial intelligence (AI) and private equity (PE) has opened up transformative opportunities for portfolio companies and investors alike. While AI is often discussed in the context of deal sourcing or due diligence, its application in value creation is where its potential truly shines. In a recent discussion, Bruce Sinclair, managing partner at AI Operating Partners, delved into how PE firms can leverage AI - particularly digital twins - to unlock growth, optimize operations, and drive returns. This article unpacks his insights and offers actionable guidance for professionals navigating this rapidly evolving space.

Understanding AI in Private Equity

Artificial intelligence is no longer just a futuristic concept; it’s becoming a critical tool for businesses across industries. For PE firms, AI presents an opportunity to approach value creation and risk mitigation with a level of precision and efficiency that was previously unattainable. However, as Sinclair emphasizes, the key to unlocking AI’s potential lies in understanding its capabilities and aligning it with business strategy.

From Science Project to Strategic Asset

One of the challenges PE firms face is treating AI as a technology experiment rather than a strategic tool. Sinclair points out that many AI initiatives fail - often because they’re driven bottom-up by tech enthusiasts rather than top-down from a strategic standpoint. To succeed, AI efforts must align with the firm’s investment thesis and be prioritized based on the value they can deliver.

Generative AI vs. Analytical AI

Sinclair highlights two primary types of AI applications:

• Generative AI: Focused on creating outputs, such as natural language generation or simulated conversations, this is the type of AI used in tools like large language models (LLMs).
• Analytical AI: Involves processing data to optimize systems, predict outcomes, or uncover efficiencies. This type of AI is particularly valuable in predictive modeling and optimization use cases.

Each type has distinct applications within portfolio companies, from automating repetitive tasks with generative AI to optimizing processes with analytical AI.

The Role of Digital Twins in AI-Driven Value Creation

A vital piece of the AI puzzle is digital twin technology, which acts as a bridge between the physical and digital worlds. According to Sinclair, a digital twin is a digital representation of a physical product, process, or system. It enables businesses to simulate, test, and optimize real-world operations in a digital environment.

Why Digital Twins Matter

Digital twins extend the reach of AI to traditional industries that might not traditionally be considered "digital-first." Whether it’s manufacturing, energy, or logistics, digital twins allow companies to:

• Simulate and optimize processes: By creating a mathematical model of a system, businesses can test improvements before implementation.
• Enhance decision-making: By analyzing vast amounts of real-time data, digital twins provide actionable insights.
• Enable AI integration: Digital twins serve as the foundation for applying advanced AI models, making physical processes more efficient and innovative.

Real-World Example: Tuning Steam Boilers

Sinclair shared a compelling case study involving a 70-year-old family-owned business that manufactures steam boilers. Using a digital twin of the combustion process, AI was employed to optimize fuel efficiency. The goal was to save customers money on natural gas while maintaining performance.

Rather than overhauling the boiler itself, an AI "autotuner" was developed to recommend adjustments to technicians. This approach not only improved operational efficiency but also introduced a subscription-based business model, creating recurring revenue streams.

AI in Action: Opportunities Across the Portfolio

AI’s potential isn’t limited to one domain - it can create value across various parts of a business. Here are three key areas where AI is making an impact in PE:

1. Revenue Growth

AI can help businesses expand market share and drive top-line growth. For example, Sinclair’s steam boiler case study illustrates how AI-enabled efficiency improvements can be a unique selling proposition, attracting more customers.

2. Cost Savings

Automation powered by AI can reduce fixed costs significantly. In another example shared by Sinclair, an online marketplace replaced repetitive business development tasks with AI agents. These agents outperformed average employees in recruiting sellers, demonstrating the potential for margin improvement.

3. Multiple Expansion

AI can enhance a company’s valuation by enabling it to achieve efficiencies or enter new markets. For instance, AI-driven insights can support strategic pivots, such as shifting from a one-time sales model to a recurring subscription service.

Overcoming Barriers to AI Adoption

Despite its potential, many PE firms remain in the early stages of AI adoption. According to Sinclair, the biggest hurdle is education. Firms often lack a clear understanding of what AI can do and how to implement it effectively.

Key Challenges:

1. Lack of Strategy Alignment
   AI initiatives often fail because they are not integrated into a firm’s broader strategy. Instead of starting with a clear understanding of business goals, firms may pursue AI for its own sake.
2. Vendor-Specific Solutions
   Engaging with technology vendors too early can result in fragmented efforts that don’t align with the firm’s needs. Sinclair advises taking a vendor-agnostic approach to ensure solutions are tailored to the portfolio.
3. Focus on Risk Over Opportunity
   While risk mitigation is an important aspect of AI adoption, focusing solely on potential threats can distract from its value-creation potential. Firms must balance caution with a forward-looking mindset.

A Practical Framework for Adoption

Ready to embrace AI? Sinclair offers a structured approach for PE firms looking to integrate AI into their portfolio strategies:

1. Educate the Firm

Start with broad education for all team members to demystify AI. This foundational understanding helps everyone - from associates to senior partners - grasp its potential.

2. Triage the Portfolio

Assess portfolio companies to identify where AI can have the greatest impact. Consider both risk and opportunity at various levels, from individual tasks to company-wide processes.

3. Engage Management Teams

Involve the leadership and technical teams at portfolio companies to uncover specific opportunities for AI implementation.

4. Focus on Value Drivers

Align AI projects with core value drivers: revenue growth, cost savings, and multiple expansion. Quantify estimated returns to prioritize initiatives effectively.

5. Execute with Precision

AI is a tool, not a magic bullet. Partner with experts who can develop actionable AI strategies and deploy them in alignment with business goals.

Key Takeaways

• Education is Essential: Understanding AI’s capabilities is the first step to leveraging it effectively.
• Start with Strategy: Align AI initiatives with the firm’s overall investment thesis and value creation goals.
• Digital Twins Unlock AI’s Potential: These tools enable AI to be applied in traditional industries by creating digital models of physical processes.
• Prioritize Value Creation: AI should be treated as a value creation tool, not a science experiment or isolated technology initiative.
• Adopt a Top-Down Approach: Begin at the strategy level and work down to implementation details like hardware or software selection.
• Focus on ROI: Quantify the impact of AI projects to ensure they deliver measurable returns.
• Balance Risk and Opportunity: While risk mitigation is important, don’t overlook AI’s potential to drive innovation and growth.

Conclusion

AI and digital twin technology represent a paradigm shift for private equity firms seeking to enhance portfolio performance. By approaching AI strategically and focusing on education, PE firms can unlock new avenues for growth, efficiency, and competitive advantage. Whether it’s optimizing traditional industries or automating repetitive tasks, the possibilities are vast - as long as firms commit to understanding and integrating AI into their value creation playbook.

Source: "Unlocking AI’s Potential for Portco Value Creation | Middle Market Growth Conversations" - Association for Corporate Growth (ACG), YouTube, Aug 25, 2025 - https://www.youtube.com/watch?v=l9mIBzc-Euk

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